docs: def get_transformed_feature_indices(features, stats):
    """Returns information about the transformed features.
  
    Returns:
      List in the from
      [(transformed_feature_name, {size: int, index_start: int})]
    """
  
    feature_indices = []
    index_start = 1
    for name, transform in sorted(six.iteritems(features)):
      transform_name = transform['transform']
      source_column = transform['source_column']
      info = {}
      if transform_name in [IDENTITY_TRANSFORM, SCALE_TRANSFORM]:
        info['size'] = 1
      elif transform_name in [ONE_HOT_TRANSFORM, MULTI_HOT_TRANSFORM]:
        info['size'] = stats['column_stats'][source_column]['vocab_size']
      elif transform_name == IMAGE_TRANSFORM:
        info['size'] = IMAGE_BOTTLENECK_TENSOR_SIZE
      elif transform_name == TARGET_TRANSFORM:
        info['size'] = 0
      else:
        raise ValueError('xgboost does not support transform "%s"' % transform)
  
      info['index_start'] = index_start
      index_start += info['size']
      feature_indices.append((name, info))
  
    return feature_indices